---
license: apache-2.0
base_model: albert-xxlarge-v2
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: albert-xxlarge-v2-disaster-twitter-preprocess_data
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# albert-xxlarge-v2-disaster-twitter-preprocess_data

This model is a fine-tuned version of [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4819
- F1: 0.7818

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.603         | 1.0   | 762  | 0.6956          | 0.0    |
| 0.5915        | 2.0   | 1524 | 0.7287          | 0.7011 |
| 0.5551        | 3.0   | 2286 | 0.5446          | 0.7629 |
| 0.4994        | 4.0   | 3048 | 0.4434          | 0.7722 |
| 0.4244        | 5.0   | 3810 | 0.4622          | 0.7840 |
| 0.4126        | 6.0   | 4572 | 0.4819          | 0.7818 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2